Imagem
squoosh
Make images smaller using best-in-class codecs, right in the browser.
★ 26,0 mil estrelasApache-2.0
Ver o guia →browserytools é um projeto de imagem de código aberto de aghyad97 (aghyad97/browserytools no GitHub). Tem 694 estrelas no GitHub e 80 forks, é publicado sob a licença AGPL-3.0 e foi atualizado pela última vez no GitHub em 19 de setembro de 2026.
152 free browser tools in 17 languages — no uploads, no accounts, no ads
Visit BrowseryTools in any modern browser.
Browse 152 tools across images, PDFs, text and more.
Everything processes in your tab — files never upload.
Download or copy the output right away.
Image, PDF, converter, formatter, calculator and AI utilities.
Processing stays in your browser, always.
Use everything without signing up or ads.
Localized UI for a global audience.
Some AI tools download model weights on first use.
Free; hosted forks must share their source.
Download the source and move into the project folder.
git clone https://github.com/aghyad97/browserytools.git
cd browserytoolsEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at aghyad97/browserytools with 162 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Yes — files are processed in your browser; nothing is uploaded.
AGPL-3.0 — you can use it, but hosting a modified version requires sharing source.
Some download model weights on first use, then run on-device.
The interface is available in 17 languages.
Make images smaller using best-in-class codecs, right in the browser.
Multi functional app to find duplicates, empty folders, similar images etc.
A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling…
AI image toolkit that runs entirely in your browser — private, free, offline-first
Privacy-first browser tool for tagging LoRA training datasets — no install
Create LoRA training datasets in the browser — Flux 2, Qwen, Nano Banana
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Focus on prompting and generating
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Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.